Industries › Fashion-Tech
Fashion-tech platforms
that hold up on drop day.
AI styling apps, connected wearables and high-load commerce backends for fashion-tech founders.
Fashion runs on spikes: a drop sells out in minutes, a viral video brings a week of traffic in an hour. We build the backends, AI pipelines and mobile apps that stay fast when that happens.
Where our fashion-tech practice stands
Fashion-Tech software development capabilities
What we build for
fashion technology companies.
Three problems we're built to solve in fashion tech.
AI Styling & Personalization
Recommendation engines, image recognition for product tagging and personal-styling assistants that learn from user behaviour. Production ML that serves personalized recommendations in real time, with monitoring and retraining built in — the stack behind FashionAI Stylist.
High-Load Commerce for Drops
Real-time inventory, checkout and payments engineered for flash drops and live-shopping spikes — built on Elixir/OTP, and integrating with the storefront you already run.
Connected Wearables & Digital Product Passport
BLE pairing, OTA updates and cloud telemetry — the same stack that runs 200,000+ connected devices, including Zipato smart-home hubs. Plus EU Digital Product Passport readiness — item-level IDs, QR/NFC data carriers, a supply-chain data model and a public product page — ready before the textile rules apply.
Featured engagement
FashionAI Stylist — a mobile AI personal stylist in your pocket.
FashionAI Stylist is a consumer mobile application that answers a daily question — what should I wear today? We're building the platform alongside the founders: backend, AI pipelines, mobile app, and the foundation it runs on.
For the AI styling engine, we chose a stack built around Python and PyTorch for the recommendation models, Elixir/OTP for the real-time backend that serves personalized outfits in milliseconds, and React Native for the cross-platform mobile experience. This combination matches the product's reality: heavy ML workloads under the hood, sub-second responsiveness on top, and a single mobile codebase across iOS and Android.
Why this stack? Python remains the de-facto language of computer vision and recommendation systems. Elixir gives us the concurrency to absorb bursts of style-recommendation requests without scaling the infrastructure budget. React Native lets a small senior team deliver feature parity on both platforms without the cost of two separate native apps.
Why fashion-tech founders work with us
Six things our long-term fashion partners stop worrying about.
What breaks in fashion tech when it grows — and how we prevent it.
Scaling without rewriting from scratch
Fashion platforms often hit Series B and discover that their original architecture can't handle 10× the load. We engineer fashion-tech systems for the scale you're heading toward — not the one you have today.
R&D cost that goes down as you grow
Properly architected fashion technology platforms get cheaper to operate as they scale. Most of our partners see 30–60% infrastructure cost reduction once we re-architect for the load patterns they actually have.
Drop day doesn't take your site down
Drops, flash sales, viral moments — fashion is a real-time business. We use the same Elixir/OTP foundation that powers WhatsApp, Discord and Klarna to keep your platform responsive when the spike actually comes.
AI and ML that ship to production
Most ML fashion projects die in the notebook. We build end-to-end inference pipelines — feature stores, model serving, monitoring, drift detection — so your AI models survive contact with real users at real scale.
Compliance ready for global expansion
GDPR-ready data handling and EU Digital Product Passport readiness built into the data model from day one — not bolted on before audit deadlines.
A senior team that won't disappear
Your project is led by a senior engineer — the same person from first call to release, never handed off to junior teams or account managers.
Proof from adjacent work
What we've already built that fashion tech needs.
Real-time sample tracking for TruLab
Item-level tracking that tells clinical trials where every biological sample is right now — the same model a Digital Product Passport needs for every garment.
3D printing management platform
50+ printer models supported and 3D orders processed in under 10 minutes — the pipeline experience behind 3D product assets.
TimeTick.io — idea to MVP in 6 months
A device-agnostic IoT monitoring platform shipped as an MVP in under six months — the pace a fashion-tech startup needs before its next round.
Frequently asked questions
Fashion-tech engineering — answered.
If your question isn't here, ask it directly — a senior engineer responds, not a sales team.
Can your backend handle a sold-out drop?
Are you ready for the EU Digital Product Passport?
Who owns the code and IP?
Discuss your fashion-tech build.
Tell us what you're building, where the system breaks under load, and what scale looks like in twelve months. A senior engineer will write back within two business days.
Prefer email? [email protected]
We work with a deliberate roster of clients each year. If we're not the right fit, we'll tell you — and point you somewhere that is.